At Hansa Cequity, we believe successful enterprises of tomorrow will be the ones who can organize and leverage customer information at speed , to optimize their marketing performance, increase accountability, improve profit and deliver growth. Hansa Cequity insights will bring to you trends and insights in this area and it's our way of sharing best practices so as to help you accelerate this culture and thinking in your organization. We call this kind of an approach Analytical Marketing and we will constantly bring in "best practices" for improving your capabilities in Analytical Marketing.

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How prostitution,alcohol & data science impact Uber ?


If you thought Uber was just a car service company, it's a tech company that happens to be a car service too. No wonder it has neuroscientists amongst more traditional hires in the company! The data team at Uber uses data science for fundamental problems such as ETA algorithms (“Your driver will be here in 5 minutes”), pricing algorithms, fare estimators, and heat maps to show passengers the current position of their driver.

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Uber‘s $1.2 billion financing tells a story- the imputed value for Uber (pre-money, i.e., prior to the influx of $1.2 billion) was $17 billion, a mind-boggling sum for a business that generates a couple of hundred million in revenues.

Both Lyft (another car sharing company) & Uber have attracted massive financing. Now that each team has a quarter-billion dollars in its pocket, the World championships can begin.

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Uber is trying to use the "movement pattern" data that it gets to more sharply understand its users. Here are 3 examples in the words of the Uber data scientists that I found fascinating:

  1. Understanding Destination choices: Where has this person gone in the past? Do they frequent a certain bar? Where do other Uber users go? What businesses are popular generally? These are the basic questions the algorithm asks. On top of that, it smartly considers factors like time of day (people don't typically go to night clubs at 11 a.m.), distance (people aren't likely to get dropped off too far from their actual destination) and even the Zip code of each destination (Sketchy neighborhood? They probably didn't want to walk far, so the destination is likely near the drop-off point).
  2. Static or dynamic drivers:In another blog post , Uber data scientist Bradley Voytek explains how Uber’s “science team” simulated a city and learned that taxi drivers can just stay parked between trips and make twice as much as those who drive around in search of passengers. Uber discovered that “drivers who are constantly, randomly moving around a simulated city travel 10-20 times the distance compared to drivers who remain stationary or gravitate back toward a demand density between trips,” Voytek writes.
  3. Prostitution, Alcohol & Uber: To examine this Uber data scientists’ looked at the correlation between the number of each type of crime and the number of trips they've done in each neighbourhood. All types of crime except murder, vehicle theft, and arson were positively correlated with number of trips. After correcting for multiple comparisons, four crimes remained significantly correlated: Prostitution,Alcohol,Theft,Burglary. In other words: The parts of San Francisco that have the most prostitution, alcohol, theft, and burglary also have the most Uber rides! Party hard but be safe, Uberites!

So once you start to see the company as a data, tech & analytics company, the possibilities really start to become huge:

  1. Uber is now going after a huge new opportunity by changing the way business users can book and expense rides on its platform. The company is launching a new offering, called “Uber for Business”, which is designed to make it easier for users to bill trips directly to their company while working. Uber is providing participating companies with a centralized dashboard which they can use to keep track of rides that have been expensed. The new product is basically an acknowledgment that many consumers have been using Uber for both personal and business use cases, but their employers didn’t have a good way to manage those expenses.
  2. Uber has also moved into the fast-food delivery industry with its new service "UberFRESH", which it claims will deliver meals from local restaurants in less than 10 minutes. Uber isn’t taking on a fleet of new driving staff for the service. Instead it’s going to use its taxi drivers to relay the food between restaurant and customer. There will also be no extra delivery cost but drivers won’t leave their car to hand over the food, customers will have to collect it from the street.

How relevant is all this to a company in any traditional business?  Here are some thoughts:

  1. It’s never too late to start embedding data based thinking in your business. Data based companies like Google, AirBnB, Uber etc will get to your industry at some point.
  2. Think about cross functional IT & business teams that are programmed like a guerrilla unit to solve specific problems.Get creative people into these roles.
  3. Introspect on what kind of people you are attracting for your analytics team-look for non traditional hires from the science field!
  4. Ask yourself whether you are keeping all your data. Storage is less expensive now. At Uber, they have got every GPS point for every trip ever taken at Uber, going back to the Trip #1
  5. One of the delights of using Uber is getting your receipt by email once your ride is done-for many businesses this could be a simple way of creating a customer experience & continuing to build a customer database.

    As city-wide urban infrastructures such as buses, taxis, public utilities and roads become digital, the datasets obtained can be used for tracking movement patterns through space and time.

    The identification, analysis and comparison of such patterns will provide greater insights on human movement and contribute to a better urban management and would be useful information for urban transport services provider. Imagine if Uber & a bunch of other companies started to share such data with other companies. There could be huge power in “community analytics”. If Coke & Uber were to cooperate by mashing up their data together, interesting opportunities could develop from such partnerships. Where people travel & when they consume can have interesting parallels.


    Data driven Lingerie=Better Products


    How can Lingerie & data have any correlation? I am sure you are asking that questions. But bear with me & don’t forget to watch the video that I have provided a link to.

    But before that, allow me to digress a bit. Almost 78% of consumers think it is hard to trust companies when it comes to use of their personal data (Orange, The Future of Digital Trust, 2014). And yet Personal data has become a currency today. All of us are leaving our data behind in a digital exhaust that has begun to worry us as consumers.

    So, the World Economic Forum is calling personal data a ‘new asset class’: “a valuable resource for the 21st century that will touch all aspects of society”. But companies will need to understand how they can gather customer information without compromising the customer’s trust!

    A recent PEW report had this to say:

    “While enthusiasts see great potential for using Big Data, privacy advocates are worried as more and more data is collected about people - both as they knowingly disclose things in such things as their postings through social media and as they unknowingly share digital details about themselves as they march through life. Not only do the advocates worry about profiling, they also worry that those who crunch Big Data with algorithms might draw the wrong conclusions about who someone is, how she might behave in the future, and how to apply the correlations that will emerge in the data analysis.”

    But some companies are finding a way where consumers share information because they get "value" in return.

    True & co is this interesting company that combines data & design to create an opportunity for consumers to share data with the company thereby improving the appropriateness of the product to the customer. True & co claims to be the first company to fit women into their favourite bra with a fit quiz – no fitting rooms, no measuring tape, no photos. The data they collect allows them to match the customer to over 6000 body types on their database.

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    Research suggests that women loathe the bra shopping experience and the massive $14B intimate apparel industry is dominated by one primarily brick-and-mortar player. So True & co uses big data to make shopping online for lingerie easier & better. They collect over Half a million data points from users to help customise the experience. Since the company launched in 2012, True & Co has collected some 7 million data points  They used this data to launch products designed using this data. Body type, implicit explicit preferences etc all mashed together to create a personalised recommendation engine.

    Do have a look at this video telling their story:

    So consumers are happy to share personal information as long as they see a “value add” for themselves. And organisations with trust-based information sharing relationships with customers will have significant competitive advantage over those with traditional data gathering relationships.


    Sexy Analytics, hard execution!


    I was speaking at IIM Lucknow last night & had a wonderful session with the MBA students about the changing nature of Marketing & how Big data & Analytics are going to play a big part in it.

    Prof Ashwani Kumar had a very interesting take on how Analytics is going to be eventually embedded across every function & not exist as just a separate specialisation.

    Prof Ashwani is doing some interesting work on Analytics at IIM Lucknow & you can have a look at his work & profile here:

    I spoke about how the changing nature of consumer behaviour is creating peta bytes of data for Marketers to analyse.And though Analytics is sexy today, companies still stuggle to adopt it & gain maximum mileage from it. So Analytics is popular but hard to execute! I also spoke about the need to bring creativity into analytics through both better "story telling" & more innovative approaches to data.


    And yet  in the words of a Gartner Analyst Doug Laney “companies have better sense of the value of office furniture than their information assets".

    I also spoke about how the stock market seems to value “Information based companies” far more than any others.But most companies don't report Customer data: imagine if we had Customer flow & Customer value data along with the regular balance sheet & cash flow statements!!

    Here is an interesting chart from Gartner which highlights the improved return on Information assets:

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    Here is a copy of my presentation:

    docs/IIM LucknowAug82014.pdf

    Doug Laney has this very interesting view

    “At Gartner, our infonomics research shows how information meets the criteria of a recognizable (balance sheet) asset. Yet, because the accounting aristocracy continues to prevent organizations from recognizing it, information continues to be managed with far less discipline than financial, physical assets or recognizable intangibles. We have also shown how organizations that are more information-centric have market-to-book values that are 200-300% higher than the S&P average”

    Marketing is also changing a lot because of the access to huge amounts of Social media based customer data.

    Not just marketing, Big data is hugely changing our world & life in fundamental ways. To see the enormity of this change, have a look at the video below...


    Precision journalism: Analytics needs to learn from journalists


    I have seen innumerable situations where bright analysts are unable to “tell stories from their data”. They have a lot of learning to do from an unrelated field-Journalism!
    Ben Fry has described it very well. Analytics or Data scientists need skills from these varied fields.

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    1. Computer Science - acquire and parse data
    2. Mathematics, Statistics, & Data Mining - filter and mine
    3. Graphic Design - represent and refine
    4. Infovis and Human-Computer Interaction (HCI) - interaction

    I believe that Analytics teams have a lot to learn from the new breed of Data journalists. They have all the above skills & also work with super deadlines!

    At Cequity, our model is unique because it tries to integrate very contrasting dimensions into one entity where the sum is larger than the parts! Having a designer’s sense with data may contrast with a statistician’s dry look at numbers!

    We seek “intersection” skills-intersection of Creative, technology, data & business! Not easy to do with highly talented people & we are attempting it!

    The interesting thing is that journalism is getting far savvier with data! I see visual data based story telling in the New York Times that is absolutely mind boggling. Even here in India, I see some lovely data visualization in the Mint!

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    But are analysts getting creative with their story telling? Visualization of data is getting democratized & it is not very difficult for analysts to be creative about this. Today we as consumers are getting far savvier about technology in our personal lives & that will impact our expectations at the work place. I am sure that savvy consumers will make data presentation so much more fun even within “enterprises”.

    I also wrote on this theme earlier here

    In the Media world,new business models are emerging in which data is a raw material for profit, impact, and insight, co-created with an audience that was formerly a passive consumer!

    In 2014, data journalism is mainstream and the market for data journalists is booming.New media outlets like and are competing for eyeballs with from the Mirror, from the Atlantic Media Group &The Economist’s DataBlog.
    The New York Times hired biologist and machine models expert Chris Wiggins, an associate professor of applied mathematics at Columbia University, as its chief data scientist.
    “At The New York Times, we produce a lot of content every day, but we also have a lot of data about the way people engage with that content,” Wiggins says. “[The Times] wanted to build out a data science function not only to curate and make available those data, but to learn from those data. In particular, the thing that the New York Times is interested in learning is: what makes for a good long-term relationship with a reader?”
    “On every desk in the newsroom, reporters are starting to understand that if you don’t know how to understand and manipulate data, someone who can will be faster than you, “said Scott Klein, a managing editor at ProPublica.He continued: Can you imagine a sports reporter who doesn’t know what an on-base percentage is? Or doesn’t know how to calculate it himself? You can now ask a version of that question for almost every beat. There are more and more reporters who want to have their own data and to analyze it themselves. Take, for example, my colleague, Charlie Ornstein. In addition to being a Pulitzer Prize-winner, he’s one of the most sophisticated data reporters anywhere. He pores over new and insanely complex data sets himself. He has hit the edge of Access’ abilities and is switching to SQL Server. His being able to work and find stories inside data independently is hugely important for the work he does.
    Read about this here:

    Maybe it is time for the Analytics profession to wake up & bring some variety into their hiring-a journalist amongst their midst, maybe!


    Test or get Fired! Harrah’s casino’s amazing philosophy


    Analytics needs a evangelist! Without such a person, you just don’t get the impact that Analytics actually is capable of providing! Mostly this evangelist needs to be right at the top, the CEO!

    Of course, some CMOs have led their organizations into embracing the practice, including John Costello, former exec VP-CMO of Home Depot; John Elkins, head of global brand and marketing at Visa International; and Cathy Lyons, CMO-exec VP at Hewlett-Packard.

    One organization which has become a huge case study in the application of a “fact” based approach to business is Harrah’s Enetrtainment!

    In 1998, as Harrah’s was about to embark on wave of expansion, their CEO Philip Satre asked Gary Loveman to take a break from Harvard to become chief operating officer of Harrah’s Entertainment. The important thing was the he was not brought in as a CMO but as the COO-he had the line authority to make changes that would impact the business!!

    “In terms of income, it was actually a pay cut,” Loveman says, since he had to forego the consulting that supplemented his income as a professor.

    He went on to develop the gaming industry’s most successful loyalty and analytics program—Total Rewards—which boasts more than 40 million members.

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    In an interesting article, Karl Taro Greenfeld  says this about Gary Loveman, who has since then also become the CEO:  the chief executive officer of Harrah’s Entertainment Inc., the largest gaming corporation in the world, sees his customers as a set of probabilities wrapped in human flesh.

    Since taking over as CEO in 2003, Loveman, 50, has relied on the numbers to build Harrah’s from a regional operator of 15 casinos to one with 39 in the U.S. and 13 more overseas.

    His first big move as COO was to start a loyalty program called Total Rewards, which became such a success -- growing to over 40 million members by 2010, the largest database of probabilities in the industry -- that by the time Satre stepped down in 2003, Loveman had become the logical choice to succeed him.

    Loveman earned a Ph.D. in economics at MIT and went on to become CEO, president, and chairman of Caesars Entertainment, owner of Harrah's casinos and other resorts worldwide.

    Loveman says there are three ways to get fired from the hotel and casino company: theft, sexual harassment, and running an experiment without a control group.

    But this seems like common sense, run experiments , see what works & scale up! And yet very few companies do it.

     Dan Ariely, a behavioral economics professor at Duke University and the author of Predictably Irrational, outlined some of the resistance to experimentation that he's come up against.

    “I’ve often tried to help companies do experiments, and usually I fail spectacularly,” Ariely writes. For a company struggling with getting a good bonus system in place, he suggested experiments or even just a survey. Management, he says, “didn’t want to add to the trouble by messing with people’s bonuses merely for the sake of learning. But the employees are already unhappy, I thought, and the experiments would have provided evidence for how to make them less so in the years to come.”

    But Gary Loveman managed to stay incredibly committed to Testing. These tests run from the use of coupons to offers of free meals or hotel stays, all designed to get customers to spend more money during their playtime.

    This is what he said when asked about the Testing culture: “We need to overcome hunch and intuition with empirical evidence. . . . We can start with a hunch or strong belief, but we act on it through experiment. We want evidence. We’ve gone from the introduction of experimentation as a technique to a culture of experimentation as a business discipline. We hire people predisposed to do this by temperament and by background. Organizationally, we’re committed—and I’m committed—to making sure we have the discipline to have the decisions we make informed by this evidence”.

    And yet we mustn’t forget that Harrah’s is not an easy business to run. Currently they have,$23 billion in long-term debt & have gone through some aggressive financial re structuring.

    And lastly we must also ask ourselves, is this kind of Analytics good for society! Keeping gamblers coming back may hurt them & cause a lot of turmoil in many lives! Doesn't analytics have a social responsibility!

    4 year view or a 20 year view


    I saw this wonderful video of Vinod Khosla interviewing Larry Page & Sergey Brin.

    4 year view or a 20 year view!!

    It raises some very interesting questions. What do companies need to do to grow? How should companies look at the Short term vs long term? Taking a 4 year view vs a 20 year view are two fundamentally different philosophies. It is difficult to solve a “big problem” in 4 years & easy to do in 20 years. Google, of course likes to take on “big problems”.

    So is Google a search company or will it be a larger Health company in the future. Or will it be an Artificial intelligence company?

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    Do have a look at this (long) but interesting video.

    So Short term vs Long term? How many traditional companies would invest in something like Google Brain- a machine learning initiative to help make computing more efficient and capable by mimicking the distributed processes of the human brain. And yet Artificial intelligence is more than 60 years old as an application area. One reason why some experts believe AI is beginning to achieve its long-imagined potential is the explosion of data on the web.

    So the question we need to ask is whether we have a 4 year view of Analytics or a 20 year view?

    Maybe this may lead to the following questions to ponder over:

    1. Does your company do analytics or does it compete with analytics?
    2. Does "deep personalisation" have a role to play in your company & industry?
    3. Do analytics team participate in deeper strategic & longer term decisions in the company?
    4. Do Analytics folk with their deep specialist background have the skills to participate in such initiatives?
    5. Will unsupervised techniques like AI begin to threaten the Analytics profession (as we know it now); will it reduce the need for data scientists?


    The Predictive shopping list & the Walmart gorilla


    The best shopping list is one you don't actually have to create. When a giant like Walmart changes its mind about running a Loyalty program, it is time to sit & take notice.

    Walmart has been synonymous with Everyday Low Prices(EDP). But unlike other supermarket chains like Kroger and Safeway, Walmart did not have a crucial marketing element-- A loyalty card.

    Now Walmart is taking a distinctly different route towards loyalty. Savings Catcher, which began with a seven-city test this spring and rolls out nationally this summer, automatically gives shoppers refunds for the difference between what they paid at Walmart and lower prices advertised by competitors.


    @WalmartLabs in Silicon Valley is planning to make shopper data and analytics from the program available to shoppers themselves, in a departure from most loyalty programs. Walmart is building capabilities that will let people search and sort their receipts, get pie charts breaking down how they spend their money, generate "predictive shopping lists," keep a running tab of in-store purchases to stay on budget, get notifications when there's a manufacturer coupon available for an item on their list, or get the best-priced bundle of items within a pre-set budget.

    More importantly, this is an interesting trend where companies are beginning to use analytics for “consumer consumption”.

    Campaign management as you know it is Dead


    There is so much talk about Customer centricity. And yet no one function in a company really owns the customer. In a service organisation (banks, Retailers etc), often Marketing plays that role. But do Marketers play this role well & are they able to do the “productive conflict” that is needed with the “lines of business” to produce a Customer oriented outcome.

    Why is it that the Campaign management team is considered a purely tactical organisation?  Across banks, telecom companies & other customer facing businesses, I often observe that Campaign management is treated as a function that is at the bottom of the Analytical marketing totem pole. And yet nothing could be further from the truth. If anything, consumers have access to a huge array of channels and tools as well as a social megaphone to reach brands. This shift firmly places the consumer in the driver’s seat. And yet the “last mile” that creates engagement with customers is considered a purely tactical function. Customer centricity needs anchoring within the organization to create more meaningful impact.

    Campaign execution is boring. If it is seen as a pure “execution “job, this function will be staffed by people who automate & run tools. I am not saying that this is not important. It is crucial to correctly engage with customers. But what is critical is to have a Customer strategy & in today’s world with real time marketing, this is becoming even more critical. Often in a bank, product managers will decide what customers to contact & with what offer. In the absence of a Customer segment strategy, the bank will continuously bombard customers with offers because each product manager will drive campaigns to the customer.

    But what if campaign management is looked at more strategically, as a "real time, customer engagement team".Mckinsey shared this wonderful infographic that truly demonstrates this new reality!

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    Do senior managers inside companies recognise this reality? Do HR leaders appreciate the need for this competency? Is there a skill level inside the organization to handle the customer strategy issues, the data issues, the campaign design issues and the reporting issues? And, as the complexity increases exponentially with testing and rapidly increased campaigns, is there the ability to scale those resources?

    Also do companies have a career path for people who do this? Marketing ranks low in sales-driven organizations, where the function’s leaders focus mostly on corporate communications and brand campaigns. Rethinking campaigns needs, a different CMO, much closer to peers on the executive team, who can deliver a Business impact. And who believes that campaign management can play a larger role.

    How can Marketing leaders make the Campaign management function more strategic? To begin with campaign management must connect to larger Customer strategy. A few key drivers can be:


    1. Support an institutional memory of the customer-different silos or “lines of business” creating campaigns & running them independently means that you do not have a centralised contact history or “intelligence” about customer response. Building this is not just an IT job of building a data mart or data warehouse. Rather it is an ongoing effort to create Customer intelligence in a central environment.
    2. Enable dialogues not just campaigns. If campaigns are seen as just “list pulls”, then anyone who knows basis SQL should be able to do the job. But the consumer is no longer ready to listen to “push marketing” & the creation of a “dialogue factory” is one essential element of a strong Customer strategy.
    3. Creating a Digital campaign management Hub : Important to develop a customer segment-based organisation structure with a single function owning customer contact strategy. This is not easy to do & many companies struggle without it. One way is to centralise the campaign management organisation which unifies inbound and outbound marketing programs. It also bridges the online and offline gaps-now Campaign management is not only about sending an email or a sms.The Digital hub therefore needs a variety of skills-traditional campaign management combined with string digital thinking.  In the Digital hub, one integrated team does: social insights, customer strategy & campaign execution across channels.

      4.    Create a Customer Intelligence Unit: Who owns client insights and the ultimate customer value proposition? Customer intelligence is different from Business intelligence.Analytics can provide a huge diffrentiator to how companies understand their customers.

      5.    Establish a strong Customer management council: group of top leaders in the company who are able to mediate to solve the issues that arise out of taking customer centric action. This council becomes a strong enabler for Campaign management playing a differentiated role.



    Wake up & smell the Customer!


    It is interesting that there is so much talk about Customer Centricity but as consumers we don’t seem to feel the effect. And yet there are mountains of content around Customer centricity & no shortage of experts that espouse a new theory (me included!!). Harvard even runs an Executive development growth called “leading growth through Customer centricity”. And yet as consumers we just don’t see the impact!

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    Main Entry:   


    Part of Speech:   



    placing the customer at the center of a company's marketing effort, focusing on customers rather than sales's 21st Century Lexicon

     HBS professor Ranjay Gulati, an expert on leadership, strategy, and organizational issues in firms, describes how companies can evolve through four levels to become more customer-centric. Customer-centric companies tracked by Gulati between 2001 and 2007 delivered shareholder returns of 150 percent while the S&P 500 delivered 14 percent.

    Gulati’s research suggests that the gaps lie in Execution...

    “As I delved deeper into companies seeking to become more customer-centric, the biggest gap I discovered was the one between awareness and action. Much to my surprise, even if an organization and its employees became consummate listeners and tried to make sense of what they were hearing, they were often immobilized to do much with their insights. Why? The more I researched, the more it became apparent that the problem had to do with internal silos. Most organizations today are still typically built around product and geography, and do not have a clear line of sight to the customer. These silos not only create proverbial blind spots for firms but also impede coordinated action toward addressing what may be identified as central for their customers”.

    So the ball drops because the responsibility for stewardship of the customer doesn’t really have a clear owner though it should be owned by the company as a whole.

    Marketers are often under pressure to create Customer centric initiatives & often that leads to a “check box” approach where the CMO checks off initiatives that can be done: launch a loyalty program, do customer Listening using Social media listening tools, create Analytics capability, focus on Customer experience etc.

    Technology vendors are also completely in love with the “customer”. Since 2012, I have been observing IBM reinforcing the theme- “Meet the new Chief Executive Customer. That’s who’s driving the new science of marketing.”

    A recent survey from Forrester again enhances the need for customer centricity, even in the Indian context

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    And yet in every company, business managers look at the customer from the eyes of their “silo” or category. In a FMCG company, you have different category leaders in marketing all decoding the customer in different ways. Banks have a different view of the customer across the credit cards, deposits & lending spaces.

    This may need CMO’s to think about the following:

    1. Think about raising the Customer agenda across the company at a senior level. People like to talk about the “customer” but it may be useful to create actionable micro programs that carry the “customer agenda” forward.
    2. Think about building a Analytical marketing competency that allows the marketing organisation to share customer insights across the organisation. Marketers have always done this using market research. How about using other data that is core to the organisation –customer’s transactional data. And then using that to create insights that business functions start to believe in.
    3. Don't buy Marketing technology blindly. Allow your customer strategy to guide your choice of technology components for Marketing
    4. Creating a Customer intelligence organisation, whether within the Marketing team or as a partner organisation. Think about the complexities of where the Analytics team will make the most impact. Marketing has a very good opportunity of being the "change agent" & owning this function.Customer organization resized 600





    Customer equity # large database


    Apparently it is not enough to be customer-focused anymore; to succeed, businesses must be customer-obsessed.

     But having a large customer database does not mean that you are focused on Customer equity.

     Today launched a fee-based membership programme called Flipkart First, as the company steps up efforts to retain customers. Under the scheme, Flipkart is offering services such as free shipping, free one-day delivery and other benefits. Flipkart, will select 75,000 customers who will get the Flipkart First service free of cost for three months.

     Amazon, the world's biggest retail store, maintains extensive records on its 59 million active customers including demographic information (phone number address, etc), receipts, wishlists, and tonnes of other data. Amazon also keeps more than 250,000 full text books available online and allows users to comment and interact on virtually every page of the website, making Amazon one of the world's largest online communities.

    This data coupled with millions of items in inventory Amazon sells each year makes for one very large database. Amazon's two largest databases combine for more than 42 terabytes of data.

    Amazon has about 59 million active customers


    It is interesting how many large customer databases exist in the US?

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    And yet India has an explosion of Customer databases? Though at an early stage, not that many companies have 50 million & more customers in their database.

    India is likely to have the second-largest Internet user base in the world, and the largest in terms of incremental growth, with 330 million to 370 million Internet users in 2015. So the large e commerce & social media players in India will have substantial customer databases.

    Telecom has been another stupendous story. The total subscriber base as of June 2013 was 903 million vis-a-vis 22.8 million total subscribers in 1999. Mobile subscribers accounting for 96.7% of total subscriber base are responsible for this phenomenal growth in telecom. The country has achieved overall teledensity of 73.5, urban teledensity of 145 and rural teledensity of 42.

    So India should be the “customer database capital of the world”

    Flipkart, which employs over 10,000 people, has about 18 million registered users with around 3.5 million daily visits

    And yet that is miniscule when you compare it to SBI, which now has 153.9 million savings bank account holders.

    Globally, Truecaller has over 45 million users. However, more than half of it, 25 million users are from India.

    India has rising levels of urbanization, rapid growth in its consumer base, and one of the most youthful demographic profiles worldwide. Almost 58 percent of the population is under 30 years of age. The urban population is already sizable, at 377 million in 2011, or 31 percent of India’s total population. 

    As per 2011 census, India has a population of 1.20  billion (120 crore), has about 1 billion (100 crore) mobile phones, 640,000 villages, 75% literacy, 2.5% (30 million) income tax payer base, 4% (50 million) passport, 12% (150 million) driving license, less than 20% (250 million) bank account, 33% (400 million) migrant labourers and 60% (750 million) very poor people i.e. they live under Rs. 100 ($2) per day income and starve at least one meal everyday

    By April 2014, about 51% population holds Aadhaar. The Aadhaar program has already achieved the critical mass as of March 2014 by assigning 600 million (60 crore) Aadhar nos.

     But how do our marketers relate to customer databases?

    1. A customer database is valuable because you know your customer by name & address-you can now reach her. But if treated like another mass medium, it actually takes away the brand equity. Brands who don’t respect the customer & spam her thru mass marketing techniques do more damage than anything else. Customer equity cannot be taken for granted.
    2.  It takes efforts to analyse your customer database. Marketers need to bring in analytics to fill the gap. But often, expectations around analytics are “unreal”. No amount of analytics can bring in “new business”. Analytics can only help bring in “new business at a lower cost”.
    3. Marketers need to learn how to add more information about customers. Most databases still have sketchy information about customers. As consumers we don’t give marketers information unless there is a valid reason for it. Gartner says: “Consumers are in a privacy paradox: They value their privacy, but will happily divulge their personal information in return for free access to a service or financial benefit”. Personal data has become a new currency of the digital age
    4. 4.    Marketing departments need to have a Chief marketing technology officer who helps them take technology decisions. Who manages the customer database & creates value out of this asset.

      5.    And a new breed of marketers who are able to connect the customer database with social media & other sources of customer information. If done well, this can lead to powerfully relevant offers that create a customer experience.

      6.    So Customer loyalty is far more than a having a database, creating a loyalty program & giving points. How many points and rewards programs are you a member of? Most don’t drive value for the customer. Despite what AIMIA & Loyalty One may say, loyalty programs are “much more than points”. Think Customer equity & be loyal to the customer, don’t ask the customer to be loyal to you first.






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